Smart Traffic Management Solution integrating Machine Learning and Internet of Things

Increase in population and trend for luxurious lifestyle has led to huge increase in the number of vehicles. This change has further fascinated the researchers to focus on smart transportation systems. Numerous applications are offered in smart transportation systems like smart parking, detecting event of accidents, smart lights, and many more. Detecting event of accidents and informing vehicles on the move is the most prominent area of research now days. Technologies such as Internet of Things (IoT), Machine Learning (ML) can help achieve goals of smart transportation system. In this research paper, a smart architecture for accident detection and information dissemination is proposed. Initially, the data is collected using IoT sensor. After data collection, decision making is made to find out whether accident has occurred or not and the associated congestion in network using ML techniques. This information is finally disbursed to the neighboring vehicles using a secure method for data communication. The vehicles after receiving this information will decide whether to continue moving or choose some alternate path for communication. This research work emphasizes results after applying ML method and evaluates the performance of method in terms of accuracy, precision, and recall.